The identification of genetic risk factors in complex diseases has shifted to rare variants s. The read-to-variant analytic pipelines are known to provide an incomplete set of variants, and need to be applied together to detect rare variants in large sample cohorts. Our study utilizes the data from the Alzheimer's Disease Sequencing Project, consisting of over 10,000 whole exome sequencing samples. Alzheimer's disease is the most common form of dementia and the 6th leading cause of death in the United States. We tested many combinations of software packages and parameters in a "workflow integration" approach. Until now this has been impossible to accomplish due to the prohibitive amounts of compute time. In this work we recovered 50% additional variants for the ADSP that were missed by the standard protocol. Correct and complete identification of such variants is the prerequisite to successful resolution of this important societal problem.
